This section is intended to introduce various aspects of the art, which may be associated with exemplary embodiments of the present technological advancement. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the technological advancement. Accordingly, it should be understood that this section should be read in this light, and not necessarily as admissions of prior art.
Recent developments in geochemical logging technology allow rapid and continuous measurements of elemental concentrations using pulsed neutron spectroscopy logging tools. Quantification of minerals using geochemical logs is important in hydrocarbon exploration, development, and production to assess and evaluate basin thermal history, reservoir quality, and diagenesis. Mineralogy logs also provide continuous measurements of rock matrix mineral concentrations for seismic attribute modeling, formation evaluation, and geomechanical modeling. Many laboratory analysis methods and techniques have been developed to quantify rock minerals using core samples which are costly to acquire and are limited in quantity and reservoir coverage. Furthermore, coring and core analysis programs are often planned and executed in field exploration and early development phases and well logs become the main data source afterwards. Recent technological advancements of pulsed neutron induced gamma ray spectroscopy logging tools enable direct measurements of an expanded list of elements that make it possible to describe the full set of mineral assemblages in both reservoir and non-reservoir rocks. Accurate interpretation of geochemical well logs requires crucial core data calibration to establish links between elemental concentrations and mineral concentrations.
There are two types of mineral log interpretation methods in the industry, matrix inversion method and multi-mineral solver method. The matrix inversion method uses core databases that consist of laboratory measured mineral and elemental concentrations from core samples. Inversion algorithms transforming elemental concentrations to mineral concentrations within the databases are first established using numerical optimization models and methods. These core-derived inversion models are subsequently used to interpret mineral logs acquired from reservoirs and fields that are not necessarily represented by core samples within the databases. This is the case for most new exploration and frontier assets in which a few exploration wells may have been drilled and a limited amount of core data is available. This interpretation approach is adopted by all logging service companies and vendors (Freedman 2014, Herron 1996, and Pemper 2006). This method also has a disadvantage that logging vendors have only limited access to core data that are available in public domain. A multi-mineral solver method is a whole rock based approach that does not require availability of large core mineralogy databases. The whole rock analysis method quantifies properties of rock matrix and fluids simultaneously using core and log data. The multi-mineral solver formulation entails that geochemical and conventional logs are combined to form a set of log response equations with matrix mineral concentrations and pore fluid volumes as unknowns. It is required that end member properties of matrix components and fluids as well as log responses be known or assumed. A linear inversion solver is applied to solve for mineral concentrations and fluid saturations. The process is often iterated manually to achieve convergence criteria (Galford 2009, Colson, 1989). Both methods do not address the challenges that chemical compositions of minerals are often not known and exhibit variations as results of deposition environments and diagenetic alterations and ion replacements across reservoirs or basins. The matrix inversion method assumes default chemical phases and compositions that are consistent with core samples within the databases. The multi-mineral method allows users to vary mineral compositions manually and it becomes a cumbersome task when the number of minerals is more than two. Multiple iterations are often required to converge to a reasonable solution.
Recent papers published by McCarty el al. (2015) describe the BestRock toolkit. BestRock uses a nonlinear approach to optimize whole-rock chemistry with mineralogy to calculate individual mineral structural formulas and trace element associations from which certain log response parameters can then be calculated. It provides refined quantities of the mineral species present in the formation, their structural formulas, and their predicted wireline log responses. FIG. 2 in McCarty et al. (2015) illustrates that the workflow interprets core data only and calculates end point log responses of the core minerals. The workflow is not designed to directly interpret well log data and it provides end point petrophysical parameters as input to multi-mineral log analysis.
McCarty et al. (2015) explains its optimization process within the non-linear solver under the heading “Optimization of Major Elements.” The elemental concentration formulation appears to be a linear system of equations. McCarty et al. (2015) is not clear on how the non-linear solver is applied in solving the mass balance equations and what type of cost function is used in the optimization process.
Cheng et al. (2014) does not have any core or log data interpretation workflows.
U.S. Pat. No. 9,310,513 describes a downhole logging system in which raw radiation detector signals are collected and transformed into amplitude and frequency and energy distribution in unit of gamma ray count per unit of time per energy channel. The technology does not perform data post-processing after data is acquired downhole to generate rock elemental concentrations.
US Patent Publication 20150260034 describes a method for determining mineralogy models of arenites and arkoses by performing linear regressions using sum of calcium and magnesium dry weights. This method is limited to only two types of minerals using two elements and linear regressions
US Patent Publication 20160266275 describes a method for quantifying minerals of rock samples using a joint inversion of two types of laboratory analytical data, DRIFT (diffuse reflectance infrared Fourier transform spectroscopy) and XRF (X-ray fluorescence), and it shows that it is capable of quantifying additional minerals than using DRIFT only.
U.S. Pat. No. 8,311,744 describes a method for estimating elemental yields and concentrations using a natural gamma ray spectrum, a fast neutron induced inelastic spectrum, and a thermal neutron induced capture spectrum and it performs spectral decomposition using a weighted sum of monoelemental spectral standards. It also uses a classifier or a classification system to receive elemental concentrations as input and to provide lithotypes as output.